A New Exponential Factor-Type Estimator for Population Distribution Function Using Dual Auxiliary Variables under Stratified Random Sampling

Abstract

In this paper, we propose a generalized class of exponential-type estimators for estimating the finite population distribution function using dual auxiliary variables under stratified sampling. The biases and mean squared errors (MSEs) of the proposed class of estimators are derived up to the first order of approximation. The empirical and theoretical study of comparisons is discussed. Four populations are taken for the support of the theoretical findings. It is observed that the proposed class of estimators performs better as compared to all other considered estimators in stratified sampling.

Improved estimation of population distribution function using twofold auxiliary information under simple random sampling

“…discussed a modified estimator under stratified random sampling, we develop estimators of the finite population distribution function [ 18 ]. suggested difference-type estimators based on auxiliary evidence [ 19 ]. recommended exponential estimator for the DF using auxiliary variables [ 20 ].…”